Towards the optimization of passive undulatory locomotion on land: mathematical and physical models.

endogenous and exogenous dynamics passive adaptability speed maximization stiffness distribution undulatory locomotion

Journal

Journal of the Royal Society, Interface
ISSN: 1742-5662
Titre abrégé: J R Soc Interface
Pays: England
ID NLM: 101217269

Informations de publication

Date de publication:
08 2023
Historique:
pmc-release: 09 08 2024
medline: 10 8 2023
pubmed: 9 8 2023
entrez: 9 8 2023
Statut: ppublish

Résumé

The current study investigates the body-environment interaction and exploits the passive viscoelastic properties of the body to perform undulatory locomotion. The investigations are carried out using a mathematical model based on a dry frictional environment, and the results are compared with the performance obtained using a physical model. The physical robot is a wheel-based modular system with flexible joints moving on different substrates. The influence of the spatial distribution of body stiffness on speed performance is also investigated. Our results suggest that the environment affects the performance of undulatory locomotion based on the distribution of body stiffness. While stiffness may vary with the environment, we have established a qualitative constitutive law that holds across environments. Specifically, we expect the stiffness distribution to exhibit either an ascending-descending or an ascending-plateau pattern along the length of the object, from head to tail. Furthermore, undulatory locomotion showed sensitivity to contact mechanics: solid-solid or solid-viscoelastic contact produced different locomotion kinematics. Our results elucidate how terrestrial limbless animals achieve undulatory locomotion performance by exploiting the passive properties of the environment and the body. Application of the results obtained may lead to better performing long-segmented robots that exploit the suitability of passive body dynamics and the properties of the environment in which they need to move.

Identifiants

pubmed: 37553994
doi: 10.1098/rsif.2023.0330
pmc: PMC10410216
doi:

Banques de données

figshare
['10.6084/m9.figshare.c.6751782']

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

20230330

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Auteurs

Basit Yaqoob (B)

Laboratory for Bioinspired, Bionic, Nano, Meta Materials and Mechanics, Department of Civil, Environmental and Mechanical Engineering, University of Trento, Trento 38122, Italy.
Laboratory of Bioinspired Soft Robotics, Center for Convergent Technologies, Istituto Italiano di Tecnologia, Genova 16163, Italy.

Emanuela Del Dottore (ED)

Laboratory of Bioinspired Soft Robotics, Center for Convergent Technologies, Istituto Italiano di Tecnologia, Genova 16163, Italy.

Alessio Mondini (A)

Laboratory of Bioinspired Soft Robotics, Center for Convergent Technologies, Istituto Italiano di Tecnologia, Genova 16163, Italy.

Andrea Rodella (A)

Department of Structural and Geotechnical Engineering, Sapienza University of Rome, Rome 00184, Italy.

Barbara Mazzolai (B)

Laboratory of Bioinspired Soft Robotics, Center for Convergent Technologies, Istituto Italiano di Tecnologia, Genova 16163, Italy.

Nicola M Pugno (NM)

Laboratory for Bioinspired, Bionic, Nano, Meta Materials and Mechanics, Department of Civil, Environmental and Mechanical Engineering, University of Trento, Trento 38122, Italy.
School of Engineering and Materials Science, Queen Mary University of London, London E1 4NS, UK.

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Classifications MeSH